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Reliable sensor deployment for network traffic surveillance

  • Li, Xiaopeng
  • Ouyang, Yanfeng
Registered author(s):

    New sensor technologies enable synthesis of disaggregated vehicle information from multiple locations. This paper proposes a reliable facility location model to optimize traffic surveillance benefit from synthesized sensor pairs (e.g., for travel time estimation) in addition to individual sensor flow coverage (e.g., for traffic volume statistics), while considering probabilistic sensor failures. Customized greedy and Lagrangian relaxation algorithms are proposed to solve this problem, and their performance is discussed. Numerical results show that the proposed algorithms solve the problem efficiently. We also discuss managerial insights on how optimal sensor deployment and surveillance benefits vary with surveillance objective and system parameters (such as sensor failure probabilities).

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    Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

    Volume (Year): 45 (2011)
    Issue (Month): 1 (January)
    Pages: 218-231

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    Handle: RePEc:eee:transb:v:45:y:2011:i:1:p:218-231
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    1. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    2. Sherali, Hanif D. & Desai, Jitamitra & Rakha, Hesham, 2006. "A discrete optimization approach for locating Automatic Vehicle Identification readers for the provision of roadway travel times," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 857-871, December.
    3. Castillo, Enrique & Menéndez, José María & Jiménez, Pilar, 2008. "Trip matrix and path flow reconstruction and estimation based on plate scanning and link observations," Transportation Research Part B: Methodological, Elsevier, vol. 42(5), pages 455-481, June.
    4. Yang, Hai & Zhou, Jing, 1998. "Optimal traffic counting locations for origin-destination matrix estimation," Transportation Research Part B: Methodological, Elsevier, vol. 32(2), pages 109-126, February.
    5. Li, Xiaopeng & Peng, Fan & Ouyang, Yanfeng, 2010. "Measurement and estimation of traffic oscillation properties," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 1-14, January.
    6. Li, Xiaopeng & Ouyang, Yanfeng, 2010. "A continuum approximation approach to reliable facility location design under correlated probabilistic disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 535-548, May.
    7. Ehlert, Anett & Bell, Michael G.H. & Grosso, Sergio, 2006. "The optimisation of traffic count locations in road networks," Transportation Research Part B: Methodological, Elsevier, vol. 40(6), pages 460-479, July.
    8. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    9. Yang, Hai & Iida, Yasunori & Sasaki, Tsuna, 1991. "An analysis of the reliability of an origin-destination trip matrix estimated from traffic counts," Transportation Research Part B: Methodological, Elsevier, vol. 25(5), pages 351-363, October.
    10. Hu, Shou-Ren & Peeta, Srinivas & Chu, Chun-Hsiao, 2009. "Identification of vehicle sensor locations for link-based network traffic applications," Transportation Research Part B: Methodological, Elsevier, vol. 43(8-9), pages 873-894, September.
    11. Gerard Cornuejols & Marshall L. Fisher & George L. Nemhauser, 1977. "Exceptional Paper--Location of Bank Accounts to Optimize Float: An Analytic Study of Exact and Approximate Algorithms," Management Science, INFORMS, vol. 23(8), pages 789-810, April.
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